As a core task and an important link in the fields of natural language understanding and
information retrieval, information extraction (IE) can structure and semanticize unstructured …

Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

Recent years have witnessed the resurgence of knowledge engineering which is featured
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …

With the development of social media, users increasingly tend to express their sentiments
(broadly including sentiment polarities, emotions and sarcasm, etc.) associated with fine …

Multimodal Named Entity Recognition (MNER) and Multimodal Relation Extraction (MRE)
necessitate the fundamental reasoning capacity for intricate linguistic and multimodal …

Multimodal information extraction (MIE) gains significant attention as the popularity of
multimedia content increases. However, current MIE methods often resort to using task …

With social media posts tending to be multimodal, Multimodal Named Entity Recognition
(MNER) for the text with its accompanying image is attracting more and more attention since …

The challenge posed by multimodal named entity recognition (MNER) is mainly two-fold:(1)
bridging the semantic gap between text and image and (2) matching the entity with its …

Abstract Multimodal Named Entity Recognition (MNER) aims to identify entities of predefined
types in text by leveraging information from multiple modalities, most notably textual and …

Multimodal Named Entity Recognition (MNER) on social media aims to enhance textual
entity prediction by incorporating image-based clues. Existing studies mainly focus on …